For our final project, we chose to help Quentin organize some information that he had been acquiring for his preliminary exam. At first, Emily and Kate had little idea what Quentin’s project was on. Quentin was quoted to say “Glycosyltransferase…it puts sugars on lots of stuff”. To unravel the mystery surrounding this enzyme, the trio worked together with a few tools that were learned during this weeks workshop.

Wordle: Generation of the wordle showed key words and phrases that hinted at the functioning of this enzyme. We used the first paragraph from wikipedia to create this wordle. End-note: The main method that Quentin used to organize his literary resources was End-Note. Emily and Kate created accounts so they could have access to the journal articles. We found that EndNote was a great tool to not only organize resources but to create in-text citations and bibliographies.

Some of the journal articles listed above pointed out how glycolsylation is a pivotal biological phenomena that allows enzymes to recognize other proteins and compounds. For example, the HIV virus uses a shield of sugars to mask itself from the immune system. In fact, some research focuses on recognition mechanisms for antibodies against the HIV virus.

Gapminder: HIV has become a pandemic in the global society. Being curious individuals, we explored some of the data available through Gapminder to see what demographics (like the Human Development Index) show strong correlation with [...]Continue Reading

I viewed the protein brain-derived neurotrophic factor (BDNF). I was surprised to see the structure derived from the crystal of the protein was a heterodimer. After discovering this little tid-bit, I wanted to see what interaction was “holding” the two peptides in the dimer. Figure 1, below illustrates the hydrogen bonding between polar residues. The most interesting interaction was with the biforkated water that hydrogen bonds with two serines; one on chain A and one on chain B. WOW!

Question: How different are plasmodium cyt. b in Pan troglodyte schenfurthii from the Okapi Wildlife Reserve?

Figure 1, below, was generated from a random sampling of data sets from camps KA, ON, and BA.

We found that the plasmodium between sites KA, BA, and ON are surprisingly diverse. We must point out that the sites were chosen first from the Okapi Wildlife reserve and then we discovered that the samples were unique to the P.t. schweinfurthii species. Wow! In fact, when viewing the radial tree, we saw that BApts1373_SGA10.1_cytb was the most distantly related sample. To see if this held true, we took another random sampling from the same three sites (below)

Again, BApts1373_SGA10.1_cytb was the most distantly related to the rest of the plasmodium! WHY? In the future, we could see if the mutation was more severe.

To further elucidate the cause of diversity among these plasmodium species, we could research the range P.t. schweinfurthii and what kind of environment they live in.

The question that our group investigated how closely related the cytB sequences from the gorillas and pan troglodyte troglodytes at site BB were. We took only the unique sequences from the sample data and ran it through the tree rendering software. Figure 1 is data from the pan troglodyte troglodyte and figure 2 is from the gorilla^3.

We interpreted the two trees to say that although there were a lot of data for the area, the sequences of the plasmodium were still very similar.

The cancer growth model can be applied to other situations that we will encounter in graduate school. We enjoyed “re-familiarizing” ourselves with Excel; specifically how to enter equations and build graphs. We got confused, but as we collaborated, we were able to work out the problem as a team: an essential skill for grad. students. WEEEEEE!